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T-Cell Dependent Immunogenicity of Protein Therapeutics: Preclinical Assessment and Mitigation Vibha Jawa

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T-Cell Dependent Immunogenicity of Protein Therapeutics: Preclinical Assessment and Mitigation Vibha Jawa University of Rhode Island DigitalCommons@URI Institute for Immunology and Informatics Faculty Institute for Immunology and Informatics (iCubed) Publications 2013 T-cell dependent immunogenicity of protein therapeutics: Preclinical assessment and mitigation Vibha Jawa Leslie P. Cousens See next page for additional authors Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. Follow this and additional works at: https://digitalcommons.uri.edu/immunology_facpubs Terms of Use All rights reserved under copyright. Citation/Publisher Attribution Jawa, V., Cousens, L.P., Awwad, M., Wakshull, E., Kropshofer, H., & De Groot, A.S. (2013). T-cell dependent immunogenicity of protein therapeutics: Preclinical assessment and mitigation. Clinical Immunology, 149(3.B), 534-555. Available at: http://dx.doi.org/10.1016/j.clim.2013.09.006 This Article is brought to you for free and open access by the Institute for Immunology and Informatics (iCubed) at DigitalCommons@URI. It has been accepted for inclusion in Institute for Immunology and Informatics Faculty Publications by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. Authors Vibha Jawa, Leslie P. Cousens, Michel Awwad, Eric Wakshull, Harald Kropshofer, and Anne S. De Groot This article is available at DigitalCommons@URI: https://digitalcommons.uri.edu/immunology_facpubs/3 Clinical Immunology (2013) 149, 534–555 available at www.sciencedirect.com Clinical Immunology www.elsevier.com/locate/yclim REVIEW T-cell dependent immunogenicity of protein therapeutics: Preclinical assessment and mitigation☆ Vibha Jawa a, Leslie P. Cousens b,1, Michel Awwad c,2, Eric Wakshull d, Harald Kropshofer e, Anne S. De Groot b,f,⁎ a Amgen, USA b EpiVax, USA c Pfizer, USA d Genentech, USA e Roche, Switzerland f University of Rhode Island, USA Received 8 July 2013; accepted with revision 14 September 2013 Available online 25 September 2013 KEYWORDS Abstract Protein therapeutics hold a prominent and rapidly expanding place among medicinal Quality-by-Design; products. Purified blood products, recombinant cytokines, growth factors, enzyme replacement T cell; factors, monoclonal antibodies, fusion proteins, and chimeric fusion proteins are all examples of Immunogenicity; therapeutic proteins that have been developed in the past few decades and approved for use in Cell-mediated immunity the treatment of human disease. Despite early belief that the fully human nature of these proteins would represent a significant advantage, adverse effects associated with immune responses to some biologic therapies have become a topic of some concern. As a result, drug developers are devising strategies to assess immune responses to protein therapeutics during both the preclinical and the clinical phases of development. While there are many factors that contribute to protein immunogenicity, T cell- (thymus-) dependent (Td) responses appear to play a critical role in the development of antibody responses to biologic therapeutics. A range of methodologies to predict and measure Td immune responses to protein drugs has been developed. This review will focus on the Td contribution to immunogenicity, summarizing Abbreviations: Td, T-cell dependent, thymus dependent; T, thymus; ADA, anti-drug antibodies; Ti, T-cell independent; APC, antigen-presenting cells; HLA, human leukocyte antigen; MHC, major histocompatibility complex; TCR, T cell receptor; Treg, regulatory T cells; FVIII, factor VIII; nTregs, natural regulatory T cells; aTreg, adaptive regulatory T cells; iTreg, induced regulatory T cells; IEDB, Immune Epitope Database Analysis Resource; IC50, 50% inhibitory concentration; ELISpot, enzyme-linked immunosorbent spot-forming; ELISA, enzyme-linked immunosorbent assay; CFSE, carboxyfluorescein succinimidyl ester; PBMC, peripheral blood mononuclear cells; ALN, artificial lymph node; ORG, unmodified original epitopes; FPX, recombinant Fc fusion protein; SFC, spot-forming cells. ☆ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. ⁎ Corresponding author at: 146 Clifford Street, Providence, RI USA. Fax: +1 401 272 7562. E-mail address: [email protected] (A.S. De Groot). 1 Denotes equal first-authorship. 2 Present affiliation: Merrimack Pharmaceuticals, USA. 1521-6616/$ - see front matter © 2013 The Authors. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clim.2013.09.006 Td immunogenicity of biologics 535 current approaches for the prediction and measurement of T cell-dependent immune responses to protein biologics, discussing the advantages and limitations of these technologies, and suggesting a practical approach for assessing and mitigating Td immunogenicity. © 2013 The Authors. Published by Elsevier Inc. All rights reserved. Contents 1. Introduction ......................................................... 535 1.1. The immunogenicity of protein therapeutics .................................... 535 2. The central role of T cells in immunogenicity ...................................... 537 2.1. The T cell contribution to antibody responses ................................... 537 2.2. T cell epitope stability and immunogenicity .................................... 537 2.3. Td immunity to therapeutic proteins ........................................ 538 2.4. The role of central and peripheral tolerance to biologics ............................. 538 3. Methods for predicting Td immune responses ...................................... 538 3.1. In silico T cell epitope-screening methods ..................................... 538 3.2. Strengths and limitations of in silico analysis.................................... 539 3.2.1. Antigen processing .............................................. 539 3.2.2. MHC affinity ................................................. 539 3.2.3. T cell phenotype ............................................... 540 3.2.4. Individual versus population-level predictions .............................. 540 3.2.5. Post-translational factors .......................................... 540 3.3. HLA binding assays .................................................. 540 3.3.1. Competition binding assays ......................................... 540 3.3.2. Direct binding assays............................................. 541 3.3.3. Real-time kinetic measurements ...................................... 541 3.4. Strengths and limitations of HLA binding assays .................................. 541 3.5. In vitro T cell assay methods for Td immunogenicity analysis. ......................... 541 3.5.1. Measurement of T cell cytokine responses................................. 541 3.5.2. T cell proliferation.............................................. 542 3.5.3. Tetramers................................................... 542 3.5.4. Naïve T cell in vitro assays ......................................... 542 3.5.5. T cell assays using whole antigens ..................................... 542 3.5.6. T cell re-stimulation assays using “exposed” donors . ......................... 542 3.5.7. Reconstitution of T cell immune responses in vitro . ......................... 542 3.6. Strengths and limitations of in vitro T cell assays for Td immunogenicity analysis ............... 543 3.7. Mouse models of in vivo Td immunogenicity of human therapeutic proteins .................. 543 3.7.1. HLA transgenic mice ............................................. 543 3.7.2. Humanized mouse models.......................................... 544 3.8. Strengths and limitations of mouse models of in vivo Td immunogenicity .................... 544 4. Applied Td immunogenicity prediction .......................................... 545 4.1. In silico prediction supported by subsequent clinical data . ......................... 545 4.2. Clinical link between MHC class II haplotype and IFN-β immunogenicity .................... 545 5. Mitigation of T cell-dependent immunogenicity ..................................... 546 5.1. Deimmunization .................................................... 547 5.2. Tolerization ...................................................... 547 6. Considerations: assessing immunogenicity of therapeutic proteins . ......................... 547 7. Conclusion .......................................................... 548 Conflict of interest statement .................................................. 549 References............................................................. 549 1. Introduction agents have entered the marketplace and have generated an estimated $99 billion in sales worldwide [1–4]. Therapeutic 1.1. The immunogenicity of protein therapeutics biologics offer the advantages of increased specificity and reduced toxicity compared to small molecules. However, when administered to patients, these protein-based drugs have the Since the approval of the first recombinant biological thera- potential to elicit immune responses that may directly impact peutic, insulin, in October 1982, more than 165 biotherapeutic drug safety, efficacy, and potency. For example, anti-drug 536 V. Jawa et al. antibodies (ADA) that develop in response to a therapeutic into patient-, disease-, or product-related categories. The protein may alter the drug's pharmacokinetic
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